Techniques for affecting a wireless signal-based positioning capability of a mobile device based on one or more onboard sensors

ABSTRACT

Various methods, apparatuses and/or articles of manufacture are provided which may, for example, be implemented to compute one or more inferences from signals generated by one or more inertial sensors or environmental sensors, detect an erroneous condition responsive to a comparison of the computed inference(s) with an initial position or a position fix, and, in response to the detection of the erroneous condition, affect at least one process at the mobile device that is used, at least in part, to obtain a position fix.

CLAIM OF PRIORITY UNDER 35 U.S.C. §119

This application claims priority under 35 USC 119 to U.S. ProvisionalApplication Ser. No. 61/549,539, filed Oct. 20, 2011, and entitled,“RECOVERY FROM POSITION OUTLIERS”, which is assigned to the assigneehereof and which is incorporated herein by reference.

BACKGROUND

1. Field

The subject matter disclosed herein relates to electronic devices, andmore particularly to methods, apparatuses and articles of manufacturefor use in a mobile device having one or more onboard sensors and awireless signal-based positioning capability.

2. Information

Satellite positioning systems (SPSs), such as the Global PositioningSystem (GPS) and the like, have enabled SPS receivers on mobile devicesto generate position estimates for the mobile devices by processingsignals received from transmitters aboard space vehicles (“SPSsignals”). A position estimate generated by an SPS receiver may bereferred to as a position fix. Typically, an SPS receiver will acquireSPS signals from four or more satellites of an SPS to generate aposition fix. The SPS receiver may use these SPS signals to estimatedistances (i.e., pseudoranges) to the four or more satellites. Thepseudoranges may then be used, along with knowledge about the locationsof the satellites, to generate the position fix for the mobile device.

When a position fix is desired, an SPS receiver of a mobile device mayperform a search for SPS signals being received from space. If the SPSreceiver has no knowledge of its current position or the currentposition of satellites of the SPS, this search may entail a full skyscan (which may be referred to herein as performing a search from a coldstart) to acquire the satellites, which can be a very complex process.Because of its complexity, attempting to search for and acquiresatellites from a cold start can consume significant energy and thusreduce battery life for a mobile device having an SPS receiver. Inaddition, in mobile devices having limited processing power, searchingfor SPS signals from a cold start can be very time consuming and thusdelay the generation of the position fix. An untimely or delayedposition fix may negatively impact applications which rely on positionknowledge.

In some systems, assistance data may be used by an SPS receiver toreduce the complexity of the search for SPS signals. If assistance datais used, a position fix may be achieved more quickly and with less powerconsumption. By reducing power consumption, battery life may beextended. Assistance data may include, for example, a rough estimate ofa current location of a mobile device, an estimate of SPS time, Dopplersearch window information, almanac and/or ephemeris data, as well asother forms of information. This assistance data may be obtained fromvarious sources including, for example, a remote location serveraccessible through a wireless communication network, a wireless basestation or access point associated with wireless communication network,information stored within the mobile device itself, and/or othersources.

While assistance data may allow a position fix to be obtained morequickly and with less energy expenditure, sometimes assistance data maybe inaccurate or erroneous. As will be appreciated, the use of faultyassistance data can negatively impact the accuracy of a resultingposition fix. In addition, it is often difficult to determine theaccuracy of assistance data before the data is used. Any resultingerrors in a position fix, therefore, may not be detected until one ormore location-based applications that use the position fix datamalfunctions.

SUMMARY

In accordance with certain aspects, a mobile device may perform a methodcomprising: determining a first positioning parameter based, at least inpart, on a wireless positioning signal received by the mobile device;determining a second positioning parameter based, at least in part, on asignal generated by a sensor of the mobile device; and affecting anindication of uncertainty with regard to at least the first positioningparameter based, at least in part, on the first positioning parameterand the second positioning parameter.

In accordance with certain other aspects, an apparatus may be providedfor use in a mobile device. Here, for example, the apparatus maycomprise: means for determining a first positioning parameter based, atleast in part, on a wireless positioning signal received by the mobiledevice; means for determining a second positioning parameter based, atleast in part, on a signal generated by a sensor of the mobile device;and means for affecting an indication of uncertainty with regard to atleast the first positioning parameter based, at least in part, on thefirst positioning parameter and the second positioning parameter.

In accordance with yet other aspects, a mobile device may be providedwhich comprises a communication interface; sensor; and one or moreprocessing units to: determine a first positioning parameter based, atleast in part, on a wireless positioning signal received by thecommunication interface; determine a second positioning parameter based,at least in part, on a signal generated by the sensor; and affect anindication of uncertainty with regard to at least the first positioningparameter based, at least in part, on the first positioning parameterand the second positioning parameter.

In accordance with still other aspects, an article of manufacture may beprovided which comprises a non-transitory computer readable mediumhaving stored therein computer implementable instructions executable byone or more processing units of a mobile device to: determine a firstpositioning parameter based, at least in part, on a wireless positioningsignal received by the mobile device; determine a second positioningparameter based, at least in part, on a signal generated by a sensor ofthe mobile device; and affect an indication of uncertainty with regardto at least the first positioning parameter based, at least in part, onthe first positioning parameter and the second positioning parameter.

In accordance with still other aspects, a mobile device may perform amethod comprising: computing one or more inferences from signalsgenerated by one or more inertial sensors or environmental sensors;detecting an erroneous condition responsive to a comparison of thecomputed one or more inferences with an initial position or a positionfix; and, in response to the detection of the erroneous condition,affecting a process at the mobile device that is used to obtain aposition fix.

In accordance with certain other aspects, an apparatus may be providedfor use in a mobile device. Here, for example, the apparatus maycomprise: means for computing one or more inferences from signalsgenerated by one or more inertial sensors or environmental sensors;means for detecting an erroneous condition responsive to a comparison ofthe computed one or more inferences with an initial position or aposition fix; and means for affecting a process at the mobile devicethat is used to obtain a position fix in response to the detection ofthe erroneous condition.

In accordance with still other aspects, a mobile device may be providedwhich comprises: one or more inertial sensors or environmental sensors;and one or more processing units to: compute one or more inferences fromsignals generated by the one or more inertial sensors or environmentalsensors; detect an erroneous condition responsive to a comparison of thecomputed one or more inferences with an initial position or a positionfix; and, in response to the detection of the erroneous condition,affect a process at the mobile device that is used to obtain a positionfix.

In accordance with yet other aspects, an article of manufacture may beprovided which comprises: a non-transitory computer readable mediumhaving stored therein computer implementable instructions executable byone or more processing units of a mobile device to: compute one or moreinferences from signals generated by the one or more inertial sensors orenvironmental sensors on a mobile device; detect an erroneous conditionresponsive to a comparison of the computed one or more inferences withan initial position or a position fix; and, in response to the detectionof the erroneous condition, affect a process at the mobile device thatis used to obtain a position fix.

BRIEF DESCRIPTION OF DRAWINGS

Non-limiting and non-exhaustive aspects are described with reference tothe following figures, wherein like reference numerals refer to likeparts throughout the various figures unless otherwise specified.

FIG. 1 is a schematic block diagram illustrating an example environmentthat includes a mobile device, in accordance with an exampleimplementation.

FIG. 2 is a schematic block diagram illustrating certain features of anexample computing platform in a mobile device, in accordance with anexample implementation.

FIG. 3 is a flow diagram illustrating an example process that may beimplemented in a computing platform of a mobile device, in accordancewith an example implementation.

FIG. 4 is a flow diagram illustrating yet another example process thatmay be implemented in a computing platform of a mobile device, inaccordance with an example implementation.

DETAILED DESCRIPTION

As illustrated by the examples herein, various methods, apparatuses andarticles of manufacture may be implemented in a mobile device having atleast one wireless signal-based positioning capability and one or moreonboard sensors.

The underlying techniques provided by the examples herein may, forexample, be implemented such that a mobile device provisioned with awireless signal-based positioning capability (e.g., one or moreprocesses, circuits, etc.) may be affected under certain conditionsbased on additional information that may be obtained using the one ormore onboard sensors (e.g., inertial sensor(s), environmentalsensor(s)).

By way of an initial example, a mobile device may be provisioned with awireless signal-based positioning capability that determines and/ormakes use of one or more positioning parameters associated with one ormore wireless positioning signals as received from one or moretransmitting devices. For example, a wireless signal-based positioningcapability may estimate a position of the mobile device by generatingand/or using one or more positioning parameters, such as, e.g., one ormore pseudoranges, one or more pseudorange rates, an estimated velocity,an estimated heading, an estimated elevation/altitude, one or moreestimated position coordinates, and/or the like or some combinationthereof.

Unfortunately, under certain conditions, one or more of the positioningparameters that may be generated and/or otherwise used by a wirelesssignal-based positioning capability may comprise one or more errors ormay be based, at least in part, on one or more errors, which may besignificant enough to reduce the effectiveness and/or reliability of allor part of a position fix and/or other estimated positioning informationregarding the mobile device. For example, an error in a pseudorange froma transmitting device and the mobile device may render a position fix orother positioning information unreliable. For example, an error in anestimated velocity and/or an estimated heading may render a position fixand/or other positioning information unreliable.

The techniques provided herein may be implemented, for example, to allowa mobile device to further consider one or more other positioningparameters associated with the mobile device but which are obtainedusing one or more onboard sensors. Thus, as described in greater detailherein, under certain conditions one or more sensor-based positioningparameters may be considered, possibly along with one or more wirelesssignal-based positioning parameters, to affect an indication ofuncertainty with regard to one or more sensor-based positioningparameters, and/or an indication of a position uncertainty with regardto the mobile device.

For example, in certain implementations a mobile device may determine afirst positioning parameter (e.g., based, at least in part, on awireless positioning signal received by the mobile device) and a secondpositioning parameter (e.g., based, at least in part, on a signalgenerated by a sensor of the mobile device), and affect an indication ofuncertainty with regard to at least the first positioning parameterbased, at least in part, on the first positioning parameter and thesecond positioning parameter. Here, for example, if a first positioningparameter specifies an estimated velocity of 5.0 km/h and the secondpositioning parameter specifies an estimated velocity measurement of 4.7km/h, then in certain instances an indication of uncertainty with regardto at least the first positioning parameter may be affected (if needed)to indicate a relatively low level of uncertainty, since the differencebetween these compared values may fall within an acceptable thresholdlevel or range (e.g., of ±0.5 km/h, and/or some applicable percentagebased threshold, etc.). Conversely, for example, if a first positioningparameter specifies estimated velocity of 100 km/h and the secondpositioning parameter specifies estimated measurement of 4.7 km/h, thenin certain instances an indication of uncertainty with regard to atleast the first positioning parameter may be affected (if needed) toindicate a relatively high level of uncertainty, since such a differencebetween these compared values clearly fall outside the exampleacceptable threshold level arrange of ±0.5 km/h, and/or some applicablepercentage based threshold, etc. Of course, as with all of the examplesprovided herein these are just a few illustrative examples which are notintended to limit claimed subject matter.

In certain further example implementations, such a mobile device may,for example, estimate a position of the mobile device (e.g., a positionfix) based, at least in part, on the first positioning parameter, andaffect an indication of position uncertainty with regard to theestimated position of the mobile device based, at least in part, on theindication of uncertainty. Thus, for example, a wireless signal-basedpositioning capability may be affected based, at least in part, on anindication of uncertainty with regard to at least the first positioningparameter, and/or in indication of a position uncertainty with regard tothe mobile device.

In certain example implementations, affecting an indication ofuncertainty may, for example, further comprise determining a differencevalue based, at least in part, on the first positioning parameter andthe second positioning parameter, and affecting the indication ofuncertainty based, at least in part, on a comparison of the differencevalue with a threshold value, e.g. as illustrated in the previousexamples.

In certain example implementations, a first positioning parameter may bebased, at least in part, on an estimated pseudorange from a transmitterof the wireless positioning signal (e.g., a satellite positioning system(SPS) signal, a terrestrial-based positioning system signal, etc.) tothe mobile device. For example, in certain implementations, a firstpositioning parameter may comprise or otherwise be based, at least inpart, on an estimated velocity, a pseudorange rate, and/or the like orsome combination thereof of the mobile device.

In certain example implementations, a second positioning parameter maybe based, at least in part, on an estimated velocity measurement and/orsome other like measurement of the mobile device that is determinedbased on one or more signals from one or more sensors. For example, incertain implementations an estimated velocity may be inferred fromsensed measurements as result of acceleration/deceleration experiencedby the mobile device, and/or a lack thereof (e.g., integrated orotherwise processed in some manner over a period of time, etc.).

In certain example implementations, a mobile device may determine amotion mode which may correspond to its motion and/or lack thereofwithin an environment based, at least in part, on one or more inertialand/or environmental sensor measurements. For example, a motion mode mayindicate that a mobile device appears to have remained stationary for aperiod of time, e.g., due to a lack of detected movements. At othertimes, a motion mode may, for example, indicate that a mobile device maybe being carried by a person who is walking, running, etc., e.g. due tothe detected movements that may be characterized as steps or strides.For example, a motion mode may indicate that a mobile device may beonboard a moving vehicle, aircraft, elevator, escalator, etc., e.g., dueto certain characterized movements, changes in elevation/altitude, etc.Accordingly, in certain example implementations, a second positioningparameter may be based, at least in part, on a motion mode of the mobiledevice and a motion mode may be based on one or more signals obtainedfrom one or more sensors. Various capabilities, such as pedometercapabilities and/or the like, which may be implemented to characterize amotion mode are well known and beyond the scope of the presentdescription.

In accordance with certain other aspects, an example mobile device maycompute one or more inferences (e.g., one or more positioningparameters, etc.) from one or more signals generated by one or moreinertial sensors and/or one or more environmental sensors. Such a mobiledevice may, for example, further detect an erroneous conditionresponsive to a comparison of the computed one or more inferences withan initial position and/or a position fix, and in response to thedetection of the erroneous condition, restart a process at the mobiledevice to obtain a position fix independently of the initial position.In certain implementations, an initial position may, for example, beobtained from and/or using assistance data that may be obtained from oneor more other devices. In certain implementations, a mobile device mayobtain all or part of a position fix based, at least in part, on anacquisition of a plurality of wireless positioning signals at the mobiledevice. In certain implementations, a mobile device may, for example,obtain all or part of a position fix using ephemeris information,almanac information, and/or the like or some combination thereof. Incertain example implementations, restarting a process at the mobiledevice to obtain a position fix may further comprise initiating a fullsky scan and/or the like to acquire one or more wireless positioningsignals.

In certain implementations, in detecting an erroneous condition a mobiledevice may, for example, compare a pseudorange rate and/or the likebased, at least in part, on an acquired wireless positioning signal(e.g., SPS signal, etc.) with a velocity inferred from processing one ormore signals generated by one or more inertial sensors. In certainimplementations, in detecting erroneous condition mobile device may, forexample, compare an inference computed from processing one or moresignals from an environmental sensor with an initial position or aposition fix.

Attention is drawn now to FIG. 1, which is a schematic block diagramillustrating an example environment 100 that includes a mobile device104, in accordance with an example implementation.

As shown, mobile device 104 comprises an apparatus 110 to provide orotherwise support mobile device positioning based, at least in part, onone or more of the techniques provided herein. Apparatus 110 mayrepresent one or more computing platforms that may communicate with oneor more computing devices 130, either directly (e.g. not shown) and/orindirectly, e.g. via one or more network(s) 120. For example, as shown,apparatus 110 may, at times, communicate with one or more computingdevice(s) 130 via with network(s) 120 over a wireless communication link122 and wired communication link 132. It should be understood that whilecommunication link 122 is illustrated as a wireless communication linkand communication link 132 is illustrated as a wired communication link,either of these communication links may comprise wired and/or wirelesscommunication links.

Network(s) 120 may comprise one or more communication systems and/ordata networks having various interconnected devices supportingcommunication between various electronic devices, such as mobile device104 and one or more computing devices 130. For example, communicationbetween computing device 130 and mobile device 104 may allow for certaindata and/or instructions to be exchanged there between. For example, incertain instances, assistance data may be obtained by mobile device 104from one or more computing devices 130. It should be kept in mind thatin certain implementations one or more computing devices 130 may beprovisioned within one or more network(s) 120.

As used herein a “mobile device” may represent any electronic devicethat may be moved about either directly or indirectly by a user withinenvironment 100. As mentioned, in certain implementations, mobile device104 may be capable of communicating with one or more computing device(s)130, and/or other like resources that may be provided within anetwork(s) 120. Here, for example, mobile device 104 may take the formof a smart phone, a tablet computer, a laptop computer, a trackingdevice, etc. In certain other implementations, mobile device 104 may beincapable of transmitting wireless signals or otherwise transmittingwired signals to other devices, but may be capable of receiving wirelesssignals, e.g., wireless positioning signals. Here, for example, mobiledevice 104 may take the form of a navigation device and/or the like.

Example environment 100 further includes one or more satellitepositioning system(s) (SPS) 150 which may transmit one or more wirelesspositioning signals, e.g. SPS signals 152, to mobile device 104. SPS 150may, for example, represent one or more Global Navigation SatelliteSystem (GNSS), one or more regional navigation satellite systems, and/orthe like or some combination thereof. Additionally, one or moreterrestrial-based positioning systems may be provided as represented byexample transmitting device(s) 140 capable of transmitting one or morewireless positioning signals, e.g., wireless positioning signals 142 allor some of which may be used for signal-based positioning. Thus, forexample, transmitting device(s) 140 may represent a wireless accesspoint, a base station, a repeater, a dedicated beacon transmittingdevice, just to name a few examples, which have known positions. SPSsignals 152 and/or wireless signals 142 may, at times, be acquired bymobile device 104 and used to estimate its position.

Attention is drawn next to FIG. 2, which is a schematic block diagramillustrating certain features of an example computing platform 200 in amobile device 104 to provide or otherwise support mobile devicepositioning, in accordance with an example implementation.

As illustrated computing platform 200 may comprise one or moreprocessing units 202 to perform data processing (e.g., in accordancewith the techniques provided herein, and/or apparatus 110, etc.) coupledto memory 204 via one or more connections 26. Processing unit(s) 202may, for example, be implemented in hardware or a combination ofhardware and software. Processing unit(s) 202 may be representative ofone or more circuits configurable to perform at least a portion of adata computing procedure or process. By way of example but notlimitation, a processing unit may include one or more processors,controllers, microprocessors, microcontrollers, application specificintegrated circuits, digital signal processors, programmable logicdevices, field programmable gate arrays, or the like, or any combinationthereof.

Memory 204 may be representative of any data storage mechanism. Memory204 may include, for example, a primary memory 204-1 and/or a secondarymemory 204-2. Primary memory 204-1 may comprise, for example, a randomaccess memory, read only memory, etc. While illustrated in this exampleas being separate from the processing units, it should be understoodthat all or part of a primary memory may be provided within or otherwiseco-located/coupled with processing unit(s) 202, or other like circuitrywithin mobile device 104. Secondary memory 204-2 may comprise, forexample, the same or similar type of memory as primary memory and/or oneor more data storage devices or systems, such as, for example, a diskdrive, an optical disc drive, a tape drive, a solid state memory drive,etc

In certain implementations, secondary memory may be operativelyreceptive of, or otherwise configurable to couple to, a non-transitorycomputer readable medium 270. Memory 204 and/or non-transitory computerreadable medium 270 may comprise instructions 272 associated with dataprocessing, e.g., in accordance with the techniques and/or exampleapparatus 110 (FIG. 1) and/or all or part of one or more exampleprocesses 300 (FIG. 3) and/or 400 (FIG. 4), as provided by way ofexample herein.

Computing platform 200 may, for example, further comprise one or morecommunication interface(s) 208. Communication interface(s) 208 may, forexample, provide connectivity to network(s) 120, computing device(s)130, one or more transmitting devices 140, and/or one or more SPS 150(FIG. 1), e.g., via one or more wired and/or wireless communicationlinks (as applicable). As illustrated here communication interface(s)208 may, for example, comprise one or more receivers 210, one or moretransmitters 212, one or more SPS receivers 218, and/or the like or somecombination thereof. Communication interface(s) 208 may implement one ormore communication protocols as may be required to support one or morewired and/or wireless communication links. Communication interface(s)208 may, in certain example instances, further comprise one or morereceivers capable of acquiring wireless positioning signals 142 from oneor more transmitting devices 140 associated with one or moreterrestrial-based positioning systems. In certain instances,communication interface 208 may also transmit wireless signals via oneor more transmitters 212 to one or more transmitting devices 140, e.g.,as part of a round trip time valuation process, etc. Further, in certainexample instances, communication interface(s) 208 may comprise an SPSreceiver 218 capable of acquiring SPS signals 152, e.g., in support ofone or more signal-based positioning capabilities.

In accordance with certain example implementations, communicationinterface(s) 208 and/or other resources in network(s) 120 may, forexample, be enabled for use with various wireless communication networkssuch as a wireless wide area network (WWAN), a wireless local areanetwork (WLAN), a wireless personal area network (WPAN), and so on. Theterm “network” and “system” may be used interchangeably herein. A WWANmay be a Code Division Multiple Access (CDMA) network, a Time DivisionMultiple Access (TDMA) network, a Frequency Division Multiple Access(FDMA) network, an Orthogonal Frequency Division Multiple Access (OFDMA)network, a Single-Carrier Frequency Division Multiple Access (SC-FDMA)network, and so on. A CDMA network may implement one or more radioaccess technologies (RATs) such as cdma2000, Wideband-CDMA (W-CDMA),Time Division Synchronous Code Division Multiple Access (TD-SCDMA), toname just a few radio technologies. Here, cdma2000 may includetechnologies implemented according to IS-95, IS-2000, and IS-856standards. A TDMA network may implement Global System for MobileCommunications (GSM), Digital Advanced Mobile Phone System (D-AMPS), orsome other RAT. GSM and W-CDMA are described in documents from aconsortium named “3rd Generation Partnership Project” (3GPP). Cdma2000is described in documents from a consortium named “3rd GenerationPartnership Project 2” (3GPP2). 3GPP and 3GPP2 documents are publiclyavailable. A WLAN may include an IEEE 802.11x network, and a WPAN mayinclude a Bluetooth network, an IEEE 802.15x, for example. Wirelesscommunication networks may include so-called next generationtechnologies (e.g., “4G”), such as, for example, Long Term Evolution(LTE), Advanced LTE, WiMAX, Ultra Mobile Broadband (UMB), and/or thelike. Additionally, communication interface(s) 208 and/or communicationinterface(s) 308 may further provide for infrared-based communicationswith one or more other devices.

SPS receiver 218 may, for example, represent any type of receivercapable of receiving SPS signals from positioning satellites andprocessing the signals to provide one or more position estimates for amobile device. SPS receiver 218 may, for example, be configured tooperate with any existing or future SPS system including, for example,the Global Positioning System (GPS), the GLONASS system, the Compasssystem, the Galileo system, the IRNSS system, the GNSS system and othersystems that use Satellite Based Augmentation Systems (SBASs) and/orGround Based Augmentations Systems (GBASs), and/or other satellitenavigation systems. In some implementations, one or more of theprocesses or techniques described herein may be implemented, eitherpartially or fully, within SPS receiver 218 or a similar structure(e.g., fully or partially within one or more processing units 202 and/orone or more processing units within SPS receiver 218, and/or the like orsome combination thereof). It should be appreciated that thearchitecture illustrated for computing platform 200 within mobile device104 represents one possible example of an architecture that may be usedin an implementation. Other architectures may alternatively be used. Itshould also be appreciated that all or part of the various devices,processes, or articles of manufacture, etc., described herein may beimplemented using any combination of software and hardware and/orfirmware, etc.

In addition to SPS receiver 218 to acquire and process signals from anSPS or receiver(s) 210/transmitter(s) 212 to acquire and process signalsfrom network(s) 120 and/or transmitting devices 140 (FIG. 1), mobiledevice 104 may comprise one or more sensors 216, which may represent oneor more environmental sensors (e.g., one or more magnetometers, one ormore temperature sensors, one or more microphones, one or morebarometers, one or more altimeters, one or more light sensors, one ormore cameras, etc.) and/or one or more inertial sensors (e.g., one ormore accelerometers, one or more gyroscopes, etc.). In a particularimplementation, an error condition, such as an outlier, may be detectedbased, at least in part, on an evaluation of one or more sensor signalsreceived at a current location with a recent position fix or otherinformation such as positioning assistance data. For example, an initialposition (e.g., rough position) or recent SPS position fix may beevaluated for consistency with one or more readings, signals orinferences drawn from one or more signals generated by one or moreenvironmental and/or one or more inertial sensors. Thus, for example, incertain implementations, if an initial position or possibly arecent/previous SPS position fix is not consistent with one or morereadings, signals or inferences (e.g., second positioning parameters)that may be drawn from one or more sensor signals, it may be presumedthat an error condition exists. In response to detection of an errorcondition, in a particular aspect, an indication of uncertainty withregard to one or more positioning parameters, a position fix, and/orother like position information may be affected in some manner. Inanother particular aspect, responsive to detection of the errorcondition in all or a portion of information obtained from acquisitionof the SPS signals at SPS receiver 218, a process to attempt tore-acquisition of SPS signals at SPS receiver 218 may be restarted orotherwise initiated or operatively affected in some manner. Here, forexample, one or more processes associated with a wireless signal-basedpositioning capability may be restarted and/or affected in some othermanner.

In certain instances it may, for example, be assumed that there is atleast a strong possibility that assistance data relied upon in obtainingthe erroneous position fix was inaccurate or erroneous. Accordingly, inanother aspect, a re-acquisition of SPS signals (e.g., followingdetection of an error condition as discussed above) may be performedwithout at least some if not all of the assistance data that was reliedupon in an initial computation of the position fix. For example, withthe presence of certain detected error conditions, there may be asignificant likelihood that assistance data such as an initial positionand/or estimate of SPS time is erroneous. Accordingly, all or part ofsuch particular assistance data may be discarded or ignored. Other datathat may be discarded or ignored, in whole or part, upon detecting anerror condition may include, for example, clock frequency, biasestimate, GNSS measurements, space vehicle steering and/or space vehicledirections. In certain instances, other assistance data, such as almanacand/or ephemeris, may be presumed to be very reliable. As such, almanacand/or ephemeris data may be used to obtain a subsequent position fix.

In certain example implementations, an error condition may be detectedfrom a comparison of one or more positioning parameters that may bebased, at least in part, on one or more acquired SPS signals with one ormore other positioning parameters that may be based, at least in part,on one or more signals obtained from one or more onboard sensors. Forexample, a pseudorange rate (PRR) and/or an estimated velocity obtainedfrom acquisition of an SPS signal at a mobile device may be comparedwith an estimated velocity measurement of the mobile device asdetermined from processing inertial sensor signals, etc. Thus, forexample, if there is a significant divergence between an estimatedvelocity and corresponding estimated velocity measurement, there may bea significant likelihood that an SPS position fix and/or other likepositioning information may be erroneous. In certain exampleimplementations, as previously mentioned, one or more threshold valuesmay be taken into consideration in detecting errors and/or erroneousconditions of varying types. It should be recognized that such thresholdvalues may be predetermined and/or dynamically determined depending uponthe implemented design. Also, as previously mentioned, in certaininstances one or more indications of uncertainty with regard to one ormore positioning parameters and/or one or more indications of positionuncertainty with regard to mobile device 104 may be affected based, atleast in part, on a detected error and/or lack thereof. In certainexample implementations, a sensor high-confidence-static vs.low-redundancy GNSS high-speed offset detection may be an effectivescheme to detect an error.

Given that the use of a full sky scan may, at times, heavily tax a powersupply (e.g., battery, etc.) of a mobile device, it may be appreciatedthat there may be a trade-off between extending or conserving theelectrical power and correcting for error conditions. Thus, in certaininstances, criteria for testing the fitness of a computed position fixand/or other like positioning information may be set or adjustedaccording to a need for preserving electrical power of a mobile device.

As further illustrated in FIG. 2, a mobile device 104 may, for example,further comprise one or more input/output units 214. Input/output units214 may represent one or more devices or other like mechanisms that maybe used to obtain inputs from and/or provide outputs to one or moreother devices and/or a user of mobile device 104. Thus, for example,input/output units 214 may comprise various buttons, switches, a touchpad, a trackball, a joystick, a touch screen, a microphone, a camera,and/or the like, which may be used to receive one or more user inputs.In certain instances, input/output units 214 may comprise variousdevices that may be used in producing a visual output, an audibleoutput, and/or a tactile output for a user. In one exampleimplementation, input/output units 214 may comprise a display capable ofrendering all or part of displayable image data and/or the like withregard to a positioning fix, a wireless signal-based positioningcapability, some aspect of environment 100, etc.

As illustrated mobile device 104 may comprise one or more processingunits 202 to perform data processing (e.g., in accordance with thetechniques provided herein) coupled to memory 204 via one or moreconnection(s) 206 (e.g., one or more conductors, one or more conductivepaths, one or more fibers, one or more buses, one or more interfaces,etc.). Processing unit(s) 202 and/or instructions 272 may, for example,provide or otherwise be associated with one or more signals that may bestored in memory 204 from time to time, such as: instructions 272;apparatus 110; one or more first positioning parameters 220 (e.g.,based, at least in part, on one or more wireless positioning signals);one or more second positioning parameters 222 (e.g., based, at least inpart, on one or more signals generated by or obtained from one or moresensors); one or more indications of uncertainty 224 (e.g., associatedwith one or more first or second positioning parameters); one or moreestimated positions 226; one or more indications of a positionuncertainty 228 (e.g., associated with one or more estimated positions,and/or other positioning information); a wireless signal-basedpositioning capability 230; a difference value 232 (e.g., based, atleast in part, on a comparison of at least a first positioning parameterwith a second positioning parameter); one or more threshold values 234;one or more (estimated) pseudoranges 236; one or more estimatedvelocities 238; one or more estimated velocity measurements 240 (e.g.,inferred from one or more sensor signals); a motion mode 242; one ormore inferences 244 (e.g. associated with an initial position and/or aposition fix, etc.); an erroneous condition 246 (e.g., possiblyassociated with one or more errors and/or lack thereof); a comparisonvalue 248; assistance data 250; a full sky scan 252 and/or other likeprocess/capability; one or more (estimated) pseudorange rates 254 (e.g.,based, at least in part, on one or more wireless positioning signals);and/or the like or some combination thereof.

Attention is drawn next to FIG. 3, which is a flow diagram illustratingan example process 300 that may be implemented in a computing platform200 of a mobile device 104, in accordance with an exampleimplementation.

At example block 302, a first positioning parameter may be determinedbased, at least in part, on a wireless positioning signal received bythe mobile device. For example, in certain implementations, one or morewireless positioning signals may be acquired from one or moreterrestrial-based transmitting devices and/or one or more SPS. As usedherein, the term “first positioning parameter” is intended to representany information that may be based, at least in part, on one or morewireless positioning signals and which may be represented by one or moreelectrical signals and which may be of use in a wireless signal-basedpositioning capability and/or other like positioning capabilitiesprovisioned within the mobile device. Thus, by way of some non-limitingexamples, a first positioning parameter may comprise or relate to one ormore of: an estimated velocity, an estimated pseudorange rate, anestimated pseudorange, an estimated elevation/altitude, a particulartime, an estimated heading, all or part of a position coordinate, and/orthe like or some combination thereof.

At example block 304, a second positioning parameter may be determinedbased, at least in part, on one or more signals generated by one or moresensors of the mobile device. Example, in certain implementations, oneor more signals may be generated by or otherwise obtained from one ormore inertial sensors on board the mobile device, and/or one or moreenvironmental sensors on board mobile device. As used herein, the term“second positioning parameter” is intended to represent any informationthat may be based, at least in part, on one or more signals from one ormore sensors and which may be represented by one or more electricalsignals and which may be of use in comparison with and/or otherwiseconsidered with respect to one or more first positioning parameters.Thus, by way of some non-limiting examples, a second positioningparameter may comprise or relate to one or more of an estimated velocitymeasurement (e.g. based on detected acceleration/deceleration over time,etc.), one or more detected movements of the mobile device withinenvironment 100, an estimated elevation/altitude (e.g., based onbarometric pressure, etc.), the particular time (e.g., day or nightbased on sensed ambient light conditions, follow-on solicited userinput, etc.), an estimated heading (e.g., based on a magnetometer, acompass capability, etc.), all or part of a position coordinate (e.g.,based on dead reckoning, follow-on solicited user input, etc.), and/orthe like or some combination thereof.

At example block 306, an indication of uncertainty with regard to atleast the first positioning parameter may be affected in some mannerbased, at least in part, on the first positioning parameter and thesecond positioning parameter. For example, an indication of uncertaintywith regard to at least a first positioning parameter may be affected(if needed) to indicate a higher or lower level of uncertainty based onan absence or presence, respectively, of a detected erroneous condition,a possible error, a failed threshold value test, etc., and/or somecombination thereof. In certain implementations, at example block 306,an implicit assumption may be that a particular second positioningparameter corresponding to a sensor is considered to be sufficientlyreliable with regard to the first positioning parameter so as to affectthe indication of uncertainty with regard to at least a firstpositioning parameter. Thus, for example, in certain implementationsrather than rely on such an implicit assumption, additional racks may beperformed to verify or otherwise ascertained that one or more secondpositioning parameters may be considered to be sufficiently reliable foruse in affecting the indication of uncertainty with regard to a firstpositioning parameter. For example, a second positioning parameter maybe compared to a corresponding reliability threshold value. For example,second positioning parameter may be considered more or less reliabledepending upon the source sensor(s), a number of sample measurementsobtained, the length of time over which sample measurements have beenobtained, etc.

In certain instances, at block 308, a wireless signal-based positioningcapability may be affected based, at least in part, on the indication ofuncertainty and/or an indication of a position uncertainty. Here, forexample, a wireless signal-based positioning capability may be restartedand/or otherwise operatively affected in some manner based, at least inpart, on such an indication of uncertainty and/or such an indication ofa position uncertainty. In certain example implementations, a wirelesssignal-based positioning capability may be determined to be in an errorstate and/or as having one or more erroneous conditions based, at leastin part, on the indication of uncertainty and/or an indication of aposition uncertainty. Thus, for example, in response to certain errorstates and/or the like mobile device 104 may initiate certain errorrecovery mechanisms. For example, an error recovery mechanism may affectand/or delete all or part of available assistance data and/or the like,and/or possibly ignore or affect all or part of new incoming assistancedata and/or the like (e.g., with the assumption that all or part of suchdata may be related in some manner to the error state). It should bekept in mind that in error state and/or the like may be declared forvarious reasons which may be unknown at the time, and possibly evenindeterminable. For example, an error state and/or the like may occurbased on data relating to an initial position, an initial time,assistance data, clock frequency, etc. accordingly, in certainimplementations, to recover from such an error state and/or the like,mobile device 104 may delete or ignore or otherwise affect certain data,restart one or more processes/capabilities

In certain instances, at block 310, a difference value may be determinedbased, at least in part, on the first positioning parameter and thesecond positioning parameter, and the indication of uncertainty may beaffected based, at least in part, on a comparison of the differencevalue with a threshold value. Thus for example, certain instances, anerroneous condition or other possible error may be detected based, atleast in part, on whether or not certain threshold tests are satisfied.

Attention is drawn next to FIG. 4, which is a flow diagram illustratingyet another example process 400 that may be implemented in a computingplatform 200 of a mobile device 104, in accordance with an exampleimplementation. At example block 402, one or more inferences may becomputed from one or more signals generated by one or more inertialsensors and/or one or more environmental sensors. Here, for example, oneor more second positioning parameters may be determined or otherwiseinferred.

At example block 404, an erroneous condition may be detected in responseto a comparison of the computed one or more inferences with an initialposition and/or one or more other position fixes. Here, for example, oneor more erroneous conditions may be detected in initial position and/orone or more position fixes by comparing one or more first positioningparameters associated there with, with one or more second positioningparameters, e.g., as computed/inferred at block 402. In certain exampleimplementations, an erroneous condition may be detected based on one ormore threshold tests, and/or the like, at block 404.

At example block 406, in response to the detection of one or moreerroneous conditions, one or more processes may be restarted and/orotherwise affected at the mobile device, e.g. to obtain a new positionfix independently of the initial position and/or some previous positionfix. Here, for example, a wireless signal-based positioning capabilityand/or other like positioning process(es) may be restarted in somemanner and/or operated in some manner to affect a full sky scan and/orother like wireless positioning signal search technique(s).

In certain example implementations, affecting the process at the mobiledevice may comprise restarting the process, e.g., in an attempt toobtain a position fix independently of the initial position. In certainother example limitations, affecting the process at the mobile devicemay comprise affecting at least a portion of assistance data used by theprocess to obtain the position fix. Here, for example, a portion ofassistance data may be ignored, modified, or possibly deleted. Incertain example implementations, affecting at least a portion ofassistance data used by the process to obtain the position fix mayfurther comprise determining that certain assistance data may havecontributed to the erroneous condition. For example, certain assistancedata may be deemed to be out of date, and/or to have erroneousinformation (e.g., based on differences to expected values, thresholdvalues, etc.) which may have contributed to erroneous condition. Inresponse to a determination that certain assistance data may havecontributed to an erroneous condition, a mobile device may, for example,permit the process to ignore all or part of the suspect assistance data,possibly affect all or part of the suspect assistance data prior to useby the process, and/or identify part of the suspect assistance data toone or more other computing devices (e.g., corresponding to a providerof such assistance data, etc.

The techniques provided herein may be implemented to allow a variety ofdifferent first and second positioning parameters and/or a correspondingthreshold values to be taken into consideration. For example asdescribed previously, parameters associated with velocity, heading,position coordinates, altitude/elevations, etc., may be compared orotherwise considered to determine whether or not certain positioninginformation may be more or less reliable. For example, as previouslymentioned, if a velocity or heading for position coordinate oraltitude/elevation based on one or more sensors seems at odds withsimilar information based on one or more wireless positioning signals,then an erroneous condition may exist.

Although the examples presented above tend to relate to individualparameters and/or other like measurements, it should be understoodhowever that in certain implementations a plurality of parameters and/orother like measurements may be taken into consideration, e.g., obtainedover a period time, etc., to possibly reduce false positives/negativesin detecting erroneous conditions and/or affecting an indication ofuncertainty with regard to one or more positioning parameters, and/oraffecting an indication of a position uncertainty with regard to themobile device.

In certain further implementations, in response to certain conditions orresults, based on the techniques herein, a mobile device may be operatedto interact with one or more other devices and/or possibly solicitinformation from its user via one or more user inputs, which may be usedto modify or otherwise affect an operation of the mobile device or oneor more processes performed therein. For example, in response to anerroneous condition, an attempt to obtain certain assistance data may beinitiated. For example, in response to an erroneous condition, certainuser input may be solicited which may help to resolve all or part oferroneous condition or otherwise affect operation of the mobile deviceor some process performed therein.

The methodologies described herein may be implemented by various meansdepending upon applications according to particular features and/orexamples. For example, such methodologies may be implemented inhardware, firmware, and/or combinations thereof, along with software. Ina hardware implementation, for example, a processing unit may beimplemented within one or more application specific integrated circuits(ASICs), digital signal processors (DSPs), digital signal processingdevices (DSPDs), programmable logic devices (PLDs), field programmablegate arrays (FPGAs), processors, controllers, micro-controllers,microprocessors, electronic devices, other devices units designed toperform the functions described herein, and/or combinations thereof.

In the preceding detailed description, numerous specific details havebeen set forth to provide a thorough understanding of claimed subjectmatter. However, it will be understood by those skilled in the art thatclaimed subject matter may be practiced without these specific details.In other instances, methods and apparatuses that would be known by oneof ordinary skill have not been described in detail so as not to obscureclaimed subject matter.

Some portions of the preceding detailed description have been presentedin terms of algorithms or symbolic representations of operations onbinary digital electronic signals stored within a memory of a specificapparatus or special purpose computing device or platform. In thecontext of this particular specification, the term specific apparatus orthe like includes a general purpose computer once it is programmed toperform particular functions pursuant to instructions from programsoftware. Algorithmic descriptions or symbolic representations areexamples of techniques used by those of ordinary skill in the signalprocessing or related arts to convey the substance of their work toothers skilled in the art. An algorithm is here, and generally, isconsidered to be a self-consistent sequence of operations or similarsignal processing leading to a desired result. In this context,operations or processing involve physical manipulation of physicalquantities. Typically, although not necessarily, such quantities maytake the form of electrical or magnetic signals capable of being stored,transferred, combined, compared or otherwise manipulated as electronicsignals representing information. It has proven convenient at times,principally for reasons of common usage, to refer to such signals asbits, data, values, elements, symbols, characters, terms, numbers,numerals, information, or the like. It should be understood, however,that all of these or similar terms are to be associated with appropriatephysical quantities and are merely convenient labels. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout this specificationdiscussions utilizing terms such as processing, computing, calculating,determining, establishing, generating, obtaining, accessing,identifying, setting, applying, affecting, associating, and/or the likemay refer to actions or processes of a specific apparatus, such as aspecial purpose computer or a similar special purpose electroniccomputing device. In the context of this specification, therefore, aspecial purpose computer or a similar special purpose electroniccomputing device is capable of manipulating or transforming signals,typically represented as physical electronic or magnetic quantitieswithin memories, registers, or other information storage devices,transmission devices, or display devices of the special purpose computeror similar special purpose electronic computing device. In the contextof this particular patent application, the term “specific apparatus” mayinclude a general purpose computer once it is programmed to performparticular functions pursuant to instructions from program software.

The terms, “and”, “or”, and “and/or” as used herein may include avariety of meanings that also are expected to depend at least in partupon the context in which such terms are used. Typically, “or” if usedto associate a list, such as A, B or C, is intended to mean A, B, and C,here used in the inclusive sense, as well as A, B or C, here used in theexclusive sense. In addition, the term “one or more” as used herein maybe used to describe any feature, structure, or characteristic in thesingular or may be used to describe a plurality or some othercombination of features, structures or characteristics. Though, itshould be noted that this is merely an illustrative example and claimedsubject matter is not limited to this example.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein.

Therefore, it is intended that claimed subject matter not be limited tothe particular examples disclosed, but that such claimed subject mattermay also include all aspects falling within the scope of appendedclaims, and equivalents thereof.

What is claimed is:
 1. A method comprising, on a mobile device:determining a first positioning parameter based, at least in part, on awireless positioning signal received by said mobile device; determininga second positioning parameter based, at least in part, on a signalgenerated by a sensor of said mobile device; and affecting an indicationof uncertainty with regard to at least said first positioning parameterbased, at least in part, on said first positioning parameter and saidsecond positioning parameter.
 2. The method as recited in claim 1, andfurther comprising, on said mobile device: estimating a position of saidmobile device based, at least in part, on said first positioningparameter; and affecting an indication of position uncertainty withregard to said estimated position of said mobile device based, at leastin part, on said indication of uncertainty.
 3. The method as recited inclaim 2, and further comprising, on said mobile device: affecting awireless signal-based positioning capability based, at least in part, onat least one of: said indication of uncertainty; or said indication of aposition uncertainty.
 4. The method as recited in claim 1, whereinaffecting said indication of uncertainty further comprises: determininga difference value based, at least in part, on said first positioningparameter and said second positioning parameter; and affecting saidindication of uncertainty based, at least in part, on a comparison ofsaid difference value with a threshold value.
 5. The method as recitedin claim 1, wherein said first positioning parameter is based, at leastin part, on an estimated pseudorange from a transmitter of said wirelesspositioning signal to said mobile device.
 6. The method as recited inclaim 1, wherein said first positioning parameter comprises an estimatedvelocity of said mobile.
 7. The method as recited in claim 1, whereinsaid second positioning parameter is based, at least in part, on anestimated velocity measurement of said mobile device.
 8. The method asrecited in claim 1, and further comprising, on said mobile device:determining a motion mode of said mobile device; and wherein said secondpositioning parameter is based, at least in part, on said motion mode ofsaid mobile device.
 9. The method as recited in claim 1, wherein saidsensor comprises at least one of: an inertial sensor; or anenvironmental sensor.
 10. The method as recited in claim 1, wherein saidwireless positioning signal comprises a satellite positioning system(SPS) signal.
 11. An apparatus for use in a mobile device, the apparatuscomprising: means for determining a first positioning parameter based,at least in part, on a wireless positioning signal received by saidmobile device; means for determining a second positioning parameterbased, at least in part, on a signal generated by a sensor of saidmobile device; and means for affecting an indication of uncertainty withregard to at least said first positioning parameter based, at least inpart, on said first positioning parameter and said second positioningparameter.
 12. The apparatus as recited in claim 11, and furthercomprising: means for estimating a position of said mobile device based,at least in part, on said first positioning parameter; and means foraffecting an indication of position uncertainty with regard to saidestimated position of said mobile device based, at least in part, onsaid indication of uncertainty.
 13. The apparatus as recited in claim12, and further comprising: means for affecting a wireless signal-basedpositioning capability based, at least in part, on at least one of: saidindication of uncertainty; or said indication of a position uncertainty14. The apparatus as recited in claim 11, and further comprising: meansfor determining a difference value based, at least in part, on saidfirst positioning parameter and said second positioning parameter; andmeans for affecting said indication of uncertainty based, at least inpart, on a comparison of said difference value with a threshold value.15. The apparatus as recited in claim 11, wherein said first positioningparameter is based, at least in part, on an estimated pseudorange from atransmitter of said wireless positioning signal to said mobile device.16. The apparatus as recited in claim 11, wherein said first positioningparameter comprises an estimated velocity of said mobile.
 17. Theapparatus as recited in claim 11, wherein said second positioningparameter is based, at least in part, on an estimated velocitymeasurement of said mobile device.
 18. The apparatus as recited in claim11, and further comprising: means for determining a motion mode of saidmobile device; and wherein said second positioning parameter is based,at least in part, on said motion mode of said mobile device.
 19. Theapparatus as recited in claim 11, wherein said sensor comprises at leastone of: an inertial sensor; or an environmental sensor.
 20. Theapparatus as recited in claim 11, wherein said wireless positioningsignal comprises a satellite positioning system (SPS) signal.
 21. Amobile device: a communication interface; a sensor; and one or moreprocessing units to: determine a first positioning parameter based, atleast in part, on a wireless positioning signal received by saidcommunication interface; determine a second positioning parameter based,at least in part, on a signal generated by said sensor; and affect anindication of uncertainty with regard to at least said first positioningparameter based, at least in part, on said first positioning parameterand said second positioning parameter.
 22. The mobile device as recitedin claim 21, said one or more processing units to further: estimate aposition of said mobile device based, at least in part, on said firstpositioning parameter; and affect an indication of position uncertaintywith regard to said estimated position of said mobile device based, atleast in part, on said indication of uncertainty.
 23. The mobile deviceas recited in claim 22, said one or more processing units to further:affect a wireless signal-based positioning capability based, at least inpart, on at least one of: said indication of uncertainty; or saidindication of a position uncertainty
 24. The mobile device as recited inclaim 21, said one or more processing units to further: determine adifference value based, at least in part, on said first positioningparameter and said second positioning parameter; and affect saidindication of uncertainty based, at least in part, on a comparison ofsaid difference value with a threshold value.
 25. The mobile device asrecited in claim 21, wherein said first positioning parameter is based,at least in part, on an estimated pseudorange from a transmitter of saidwireless positioning signal to said mobile device.
 26. The mobile deviceas recited in claim 21, wherein said first positioning parametercomprises an estimated velocity of said mobile.
 27. The mobile device asrecited in claim 21, wherein said second positioning parameter is based,at least in part, on an estimated velocity measurement of said mobiledevice.
 28. The mobile device as recited in claim 21, said one or moreprocessing units to further: determine a motion mode of said mobiledevice; and wherein said second positioning parameter is based, at leastin part, on said motion mode of said mobile device.
 29. The mobiledevice as recited in claim 21, wherein said sensor comprises at leastone of: an inertial sensor; or an environmental sensor.
 30. The mobiledevice as recited in claim 21, wherein said wireless positioning signalcomprises a satellite positioning system (SPS) signal.
 31. An articlecomprising: a non-transitory computer readable medium having storedtherein computer implementable instructions executable by one or moreprocessing units of a mobile device to: determine a first positioningparameter based, at least in part, on a wireless positioning signalreceived by said mobile device; determine a second positioning parameterbased, at least in part, on a signal generated by a sensor of saidmobile device; and affect an indication of uncertainty with regard to atleast said first positioning parameter based, at least in part, on saidfirst positioning parameter and said second positioning parameter. 32.The article as recited in claim 31, said computer implementableinstructions being further executable by said one or more processingunits to: estimate a position of said mobile device based, at least inpart, on said first positioning parameter; and affect an indication ofposition uncertainty with regard to said estimated position of saidmobile device based, at least in part, on said indication ofuncertainty.
 33. The article as recited in claim 32, said computerimplementable instructions being further executable by said one or moreprocessing units to: affect a wireless signal-based positioningcapability based, at least in part, on at least one of: said indicationof uncertainty; or said indication of a position uncertainty
 34. Thearticle as recited in claim 31, said computer implementable instructionsbeing further executable by said one or more processing units to:determine a difference value based, at least in part, on said firstpositioning parameter and said second positioning parameter; and affectsaid indication of uncertainty based, at least in part, on a comparisonof said difference value with a threshold value.
 35. The article asrecited in claim 31, wherein said first positioning parameter is based,at least in part, on an estimated pseudorange from a transmitter of saidwireless positioning signal to said mobile device.
 36. The article asrecited in claim 31, wherein said first positioning parameter comprisesan estimated velocity of said mobile.
 37. The article as recited inclaim 31, wherein said second positioning parameter is based, at leastin part, on an estimated velocity measurement of said mobile device. 38.The article as recited in claim 31, said computer implementableinstructions being further executable by said one or more processingunits to: determine a motion mode of said mobile device; and whereinsaid second positioning parameter is based, at least in part, on saidmotion mode of said mobile device.
 39. The article as recited in claim31, wherein said sensor comprises at least one of: an inertial sensor;or an environmental sensor.
 40. The article as recited in claim 31,wherein said wireless positioning signal comprises a satellitepositioning system (SPS) signal.
 41. A method comprising, on a mobiledevice: computing one or more inferences from signals generated by oneor more inertial sensors or environmental sensors; detecting anerroneous condition responsive to a comparison of said computed one ormore inferences with an initial position or a position fix; and inresponse to said detection of said erroneous condition, affecting aprocess at said mobile device that is used to obtain a position fix. 42.The method as recited in claim 41, wherein affecting said process atsaid mobile device further comprises: restarting said process to obtainsaid position fix independently of said initial position.
 43. The methodas recited in claim 41, wherein affecting said process at said mobiledevice further comprises: affecting at least a portion of assistancedata used by said process to obtain said position fix.
 44. The method asrecited in claim 43, wherein affecting at least a portion of assistancedata used by said process to obtain said position fix further comprises:determining that certain assistance data contributed to said erroneouscondition; and at least one of: with said process, ignoring said certainassistance data; affecting said certain assistance data prior to use bysaid process; or identifying said certain assistance data to one or moreother computing devices.
 45. The method as recited in claim 41, whereinsaid initial position is obtained from assistance data.
 46. The methodas recited in claim 41, wherein affecting said process that is used toobtain said position fix further comprises: obtaining said position fixbased, at least in part, on acquisition of a plurality of SPS signals atsaid mobile device.
 47. The method as recited in claim 46, whereinobtaining said position fix further comprises obtaining said positionfix using ephemeris and/or almanac information.
 48. The method asrecited in claim 41, wherein said affecting said process at said mobiledevice that is used to obtain said position fix further comprises:initiating a full sky scan to acquire one or more satellite positioningsystem (SPS) signals.
 49. The method as recited in claim 41, whereinsaid detecting said erroneous condition further comprises: comparing apseudorange rate of an acquired satellite positioning system (SPS)signal with a velocity inferred from processing a signal generated by aninertial sensor.
 50. The method as recited in claim 41, wherein saiddetecting said erroneous condition further comprises comparing aninference computed from processing one or more signals from anenvironmental sensor with said initial position or position fix.
 51. Anapparatus for use in a mobile device, the apparatus comprising: meansfor computing one or more inferences from signals generated by one ormore inertial sensors or environmental sensors; means for detecting anerroneous condition responsive to a comparison of said computed one ormore inferences with an initial position or a position fix; and inresponse to said detection of said erroneous condition, means foraffecting a process at said mobile device that is used to obtain aposition fix.
 52. The apparatus as recited in claim 51, and furthercomprising: means for restarting said process to obtain said positionfix independently of said initial position in response to said detectionof said erroneous condition.
 53. The method as recited in claim 51, andfurther comprising: means for affecting at least a portion of assistancedata used by said process to obtain said position fix in response tosaid detection of said erroneous condition.
 54. The apparatus as recitedin claim 53, and further comprising: means for determining that certainassistance data contributed to said erroneous condition; and at leastone of: means for ignoring said certain assistance data by said process;means for affecting said certain assistance data prior to use by saidprocess; or means for identifying said certain assistance data to one ormore other computing devices.
 55. The apparatus as recited in claim 51,wherein said initial position is obtained from assistance data.
 56. Theapparatus as recited in claim 51, and further comprising: means forobtaining said position fix based, at least in part, on acquisition of aplurality of SPS signals at said mobile device.
 57. The apparatus asrecited in claim 56, and further comprising: means for obtaining saidposition fix using ephemeris and/or almanac information.
 58. Theapparatus as recited in claim 51, and further comprising: means forinitiating a full sky scan to acquire one or more satellite positioningsystem (SPS) signals.
 59. The apparatus as recited in claim 51, furthercomprising: means for comparing a pseudorange rate of an acquiredsatellite positioning system (SPS) signal with a velocity inferred fromprocessing a signal generated by an inertial sensor.
 60. The apparatusas recited in claim 51, and further comprising: means for comparing aninference computed from processing one or more signals from anenvironmental sensor with said initial position or position fix.
 61. Amobile device comprising: one or more inertial sensors or environmentalsensors; and one or more processing units to: compute one or moreinferences from signals generated by said one or more inertial sensorsor environmental sensors; detect an erroneous condition responsive to acomparison of said computed one or more inferences with an initialposition or a position fix; and in response to said detection of saiderroneous condition, affect a process at said mobile device that is usedto obtain a position fix.
 62. The mobile device as recited in claim 61,said one or more processing units to further: restart said process toobtain said position fix independently of said initial position inresponse to said detection of said erroneous condition.
 63. The mobiledevice as recited in claim 61, said one or more processing units tofurther: affect at least a portion of assistance data used by saidprocess to obtain said position fix in response to said detection ofsaid erroneous condition.
 64. The mobile device as recited in claim 63,said one or more processing units to further: determine that certainassistance data contributed to said erroneous condition; and at leastone of: with said process, ignore said certain assistance data; affectsaid certain assistance data prior to use by said process; or initiateidentification of said certain assistance data to one or more othercomputing devices.
 65. The mobile device as recited in claim 61, whereinsaid initial position is obtained from assistance data.
 66. The mobiledevice as recited in claim 61, and further comprising: a communicationinterface; and said one or more processing units to further obtain saidposition fix based, at least in part, on acquisition of a plurality ofsatellite positioning system (SPS) signals using said communicationinterface.
 67. The mobile device as recited in claim 66, said one ormore processing units to further obtain said position fix usingephemeris and/or almanac information.
 68. The mobile device as recitedin claim 61, said one or more processing units to further initiate afull sky scan to acquire one or more satellite positioning system (SPS)signals.
 69. The mobile device as recited in claim 61, said one or moreprocessing units to further compare a pseudorange rate of an acquiredSPS signal with a velocity inferred from processing a signal generatedby an inertial sensor.
 70. The mobile device as recited in claim 61,said one or more processing units to further compare an inferencecomputed from processing one or more signals from an environmentalsensor with said initial position or position fix.
 71. An articlecomprising: a non-transitory computer readable medium having storedtherein computer implementable instructions executable by one or moreprocessing units of a mobile device to: compute one or more inferencesfrom signals generated by said one or more inertial sensors orenvironmental sensors on a mobile device; detect an erroneous conditionresponsive to a comparison of said computed one or more inferences withan initial position or a position fix; and in response to said detectionof said erroneous condition, affect a process at said mobile device thatis used to obtain a position fix.
 72. The article as recited in claim71, said computer implementable instructions being further executable bysaid one or more processing units to: restart said process to obtainsaid position fix independently of said initial position in response tosaid detection of said erroneous condition.
 73. The article as recitedin claim 71, said computer implementable instructions being furtherexecutable by said one or more processing units to: affect at least aportion of assistance data used by said process to obtain said positionfix in response to said detection of said erroneous condition.
 74. Thearticle as recited in claim 73, said computer implementable instructionsbeing further executable by said one or more processing units to:determine that certain assistance data contributed to said erroneouscondition; and at least one of: with said process, ignore said certainassistance data; affect said certain assistance data prior to use bysaid process; or initiate identification of said certain assistance datato one or more other computing devices.
 75. The article as recited inclaim 71, wherein said initial position is obtained from assistancedata.
 76. The article as recited in claim 71, said computerimplementable instructions being further executable by said one or moreprocessing units to: obtain said position fix based, at least in part,on acquisition of a plurality of SPS signals at said mobile device. 77.The article as recited in claim 76, said computer implementableinstructions being further executable by said one or more processingunits to: obtain said position fix using ephemeris and/or almanacinformation.
 78. The article as recited in claim 71, said computerimplementable instructions being further executable by said one or moreprocessing units to: initiate a full sky scan to acquire one or moresatellite positioning system (SPS) signals.
 79. The article as recitedin claim 71, said computer implementable instructions being furtherexecutable by said one or more processing units to: compare apseudorange rate of an acquired SPS signal with a velocity inferred fromprocessing a signal generated by an inertial sensor.
 80. The article asrecited in claim 71, said computer implementable instructions beingfurther executable by said one or more processing units to: compare aninference computed from processing one or more signals from anenvironmental sensor with said initial position or position fix.